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StringDistances.jl
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matthieugomez 2020-02-12 09:58:03 -05:00
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@ -29,8 +29,8 @@ where `s1` and `s2` can be any iterator with a `length` method (e.g. `AbstractSt
- The package includes distance "modifiers", that can be applied to any distance.
- [Winkler](https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance) boosts the similary score of strings with common prefixes. The Winkler adjustment was originally defined for the Jaro similarity score but this package defines it for any string distance.
- [Partial](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/) returns the maximal similarity score between the shorter string and substrings of the longer string.
- [Winkler](https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance) diminishes the distance of strings with common prefixes. The Winkler adjustment was originally defined for the Jaro similarity score but this package defines it for any string distance.
- [Partial](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/) returns the minimum distance between the shorter string and substrings of the longer string.
- [TokenSort](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/) adjusts for differences in word orders by reording words alphabetically.
- [TokenSet](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/) adjusts for differences in word orders and word numbers by comparing the intersection of two strings with each string.
- [TokenMax](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/) combines scores using the base distance, the `Partial`, `TokenSort` and `TokenSet` modifiers, with penalty terms depending on string lengths.
@ -48,14 +48,15 @@ evaluate(TokenSet(Jaro()), "martha", "marhta")
evaluate(TokenMax(RatcliffObershelp()), "martha", "marhta")
```
A good distance to match strings composed of multiple words (like addresses) is `TokenMax(Levenshtein())` (see [fuzzywuzzy](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/)).
Alternatively, each `dist` struct can be used as a callable to call the evaluate function of each metric or modified metric, for example:
Alternatively, each distance can be used as a callable to call the evaluate function of each metric or modified metric, for example:
```julia
Jaro()("martha", "marhta")
Winkler(Jaro())("martha", "marhta")
QGram(2)("martha", "marhta")
```
A good distance to match strings composed of multiple words (like addresses) is `TokenMax(Levenshtein())` (see [fuzzywuzzy](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/)).
## Compare
The function `compare` is defined as 1 minus the normalized distance between two strings. It always returns a number between 0 and 1: a value of 0 means completely different and a value of 1 means completely similar.
```julia